We develop a fusion of logical and metrical principles for reasoning about Markov processes. More precisely, we lift metrics from processes to sets of processes satisfying a formula and explore how the satisfaction relation behaves as sequences of processes and sequences of formulas approach limits. A key new concept is dynamically-continuous metric bisimulation which is a property of (pseudo)metrics. We prove theorems about satisfaction in the limit, robustness theorems as well as giving a topological characterization of various classes of formulas. This work is aimed at providing approximate reasoning principles for Markov processes. © 2012 Springer-Verlag.
CITATION STYLE
Larsen, K. G., Mardare, R., & Panangaden, P. (2012). Taking it to the limit: Approximate reasoning for markov processes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7464 LNCS, pp. 681–692). https://doi.org/10.1007/978-3-642-32589-2_59
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